Add instructions on how to setup a Lambda with CodeGuru Profiler.

Author: mirelap-amazon

sample-demo-lambda-app/README.md

@@ -1,9 +1,73 @@
 # Amazon CodeGuru Profiler Python Demo Lambda Application
 
-Here's a sample code you can run in a Python Lambda in your account. Further instructions will follow soon.
-
-To enable Amazon CodeGuru Profiler, follow these instructions:
+To enable Amazon CodeGuru Profiler for a Lambda application, follow these instructions:
 * For Python 3.8: Enable `Code Profiling` for your Lambda's configuration in the `Monitoring and operation tools` tab: https://docs.aws.amazon.com/codeguru/latest/profiler-ug/setting-up-short.html#setting-up-step-2
 
 * For Python 3.6+: Follow these instructions for enabling Profiler https://docs.aws.amazon.com/codeguru/latest/profiler-ug/python-lambda.html
 
+Here's a sample code you can run in a Python Lambda in your account. You can follow the instructions to have a Python Lambda deployed in your account with CodeGuru Profiler enabled.
+
+### Create resources
+
+First step is to create the resources needed to run the application.
+
+* Go to the S3 console, create an S3 bucket and take a note of the name.
+    * Example of the name: profiler-python-recommendations-demo
+
+* Create a IAM role with these permissions to be used by the Lambda application
+    * Choose Lambda to allow our lambda functions to call AWS services on your behalf.
+    * Choose AWSLambdaBasicExecutionRole.
+    * Create an inline policy and name it profiler-python-recommendations-demo-policy.
+    * Name the role profiler-python-recommendations-demo-role.
+```
+{
+        "Version": "2012-10-17",
+        "Statement": [
+            {
+                "Sid": "VisualEditor0",
+                "Effect": "Allow",
+                "Action": [
+                    "s3:PutObject",
+                    "cloudwatch:PutMetricData"
+                ],
+                "Resource": "*"
+            }
+        ]
+    }
+```
+* Create a Lambda with the following configuration:
+    * Name: profiler-python-recommendations-demo.
+    * Runtime: Python 3.8.
+    * Change the default execution role to the newly created one.
+    * Add environment variable S3_BUCKET with the value of the bucket name that was just created.
+    * Update timeout to 10 seconds.
+* Copy-paste the code from this repository from `lambda_function.py`in the `lambda_function.py` file directly in the Lambda console in the Code tab.
+
+### Run the application
+
+Now, let’s run the application.
+
+* Run Deploy and Test.
+    * The Lambda should be successful and print some logs.
+    * You can also check the published metrics in the CloudWatch console.
+* Configure it to run every 1 minute.
+    * Click “Add trigger”.
+    * Choose EventBridge (Cloudwatch Events).
+    * Create a new rule named “profiler-python-recommendations-demo-rule”.
+    * Set schedule expression to “rate(1 minute)”.
+    * Click “Add”.
+* You can check now the Monitor tab to see the CloudWatch metrics about invocations, duration, success and others.
+* You can also go to the Cloudwatch console and see the metrics the application is publishing in the customer namespace as part of the code.
+
+### Enable code profiling
+
+* Enable code profiling by using the [automated onboarding process for Lambda](https://aws.amazon.com/about-aws/whats-new/2021/07/amazon-codeguru-profiler-announces-automated-onboarding-process-aws-lambda-functions/).
+    * Go to the Configuration tab.
+    * Click Monitoring and operations tools.
+    * Click Edit and enable “Code profiling”.
+
+### Analyzing the application
+
+Go to the Monitor tab for your Lambda and then click “View profiles in CodeGuru”. Your profiling group’s name will be the same as your Lambda’s name.
+
+Wait for 15 minutes for CodeGuru Profiler to aggregate and show the data and approximately 1 hour for the recommendations.